کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
385325 | 660864 | 2008 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Automatic feature-queried bird identification system based on entropy and fuzzy similarity
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Birdwatching is one of the very interesting hobbies and most important work. Many birdwatching assistant systems have been developed. However, most of them do not have any intelligence and cannot tolerate noises either. A bird identification system, BirdID is proposed and implemented. To identify birds, BirdID imitates bird experts to automatically direct birdwatchers to provide features. It also tries to list the most likely species after each feature is entered. In BirdID, entropy and fuzzy similarity are used to select most appropriate queried features and calculate similarity, respectively, which makes BirdID more intelligent and noise-tolerant. The experiments on a dataset with 106 species show that BirdID works well.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 34, Issue 4, May 2008, Pages 2879–2884
Journal: Expert Systems with Applications - Volume 34, Issue 4, May 2008, Pages 2879–2884
نویسندگان
Xingqi Wang, Thorsten Schiner, Xin Yao,